Teaching Ethics in a Statistics Curriculum with a Cross-Cultural Emphasis

Like most professional disciplines, the ASA has adopted ethical guidelines for its practitioners. To promote these guidelines, as well as to meet governmental and institutional mandates, U.S. universities are demanding more training on ethics within existing statistics graduate student curricula. Most of this training is based on the teachings of Western philosophers. However, many statistics graduate students are from Eastern cultures (particularly Chinese), and cultural and linguistic evidence indicates that Western ethics may be difficult to translate into the philosophical concepts common to students from different cultural backgrounds. This article describes how to teach cross-cultural ethics, with emphasis on the ASA Ethical Guidelines, within a graduate-level statistical consulting course. In particular, we present content that can help students overcome cultural and language barriers to gain an understanding of ethical decision-making that is compatible with both Western and Eastern philosophical models. Supplementary materials for this article are available online.     

Response

This article focuses on the roles consulting units can play in statistics departments, universities, and the statistics profession. An opinion on what constitutes legitimate academic activity is given. The roles endorsed are consistent with the view that statistics is both a science and an integral part of scientific methodology and hence that statistics departments need to be concerned with both the development of new methods and the proper application of those methods in the pure and applied sciences. Consulting units serve as an interface between the developers and users of statistical methodology. Communication between developers and users can be carried on effectively through consultants who are actively involved in the education of users and in the education of statistics students, either formally or informally. Such communication is also enhanced when consultants are publishing in both statistics and nonstatistics journals. Routine data analysis is not endorsed as a justifiable academic activity for consulting faculty. Supervision of graduate students on such analyses, however, can be justified. The success a consulting unit can have in playing its roles depends on appropriate funding, staffing, and administration of the unit.     

Teaching Communication in a Statistical Collaboration Course: A Feasible,Project-Based,Multimodal Curriculum

Many schools offer a statistical collaboration curriculum using standard instructional methods such as lectures whereby students are taught to successfully apply their training. The process of building statisticians' collaborative skills and characteristics can be challenging due to logistical issues, time constraints, unstructured research problems, and resources. Instructors vary in their pedagogy and topics taught, and students' experiences vary. There is a dearth of literature describing how to implement a course integrating communication skills, critical thinking, collaboration, and the integration of team members in a learner-centered format. Few courses integrate behavior-based learning using role-playing, video demonstration and feedback, case-based teaching activities, and presentation of basic statistical concepts. We have developed and implemented a two-semester biostatistics collaboration course, of which the purpose is to develop the students' knowledge, skills, attitudes, and behaviors necessary to interact effectively with investigators. Our innovative curriculum uses a multimodal, project-based, experiential process to address real-world problems provided by real and/or simulated collaborators while minimizing usual challenges. Rubrics and peer evaluation forms are offered as online supplementary materials. This article describes how a collaboration curriculum focusing on communication and team practice is feasible, how it enhances skill and professionalism, and how it can be implemented at other institutions.     

Strategies for Success: Early-Stage Collaborating Biostatistics Faculty in an Academic Health Center

Collaborative biostatistics faculty (CBF) are increasingly valued by academic health centers (AHCs) for their role in increasing success rates of grants and publications, and educating medical students and clinical researchers. Some AHCs have a biostatistics department that consists of only biostatisticians focused on methodological research, collaborative research, and education. Others may have a biostatistics unit within an interdisciplinary department, or statisticians recruited into clinical departments. Within each model, there is also variability in environment, influenced by the chair's background, research focus of colleagues, type of students taught, funding sources, and whether the department is in a medical school or school of public health. CBF appointments may be tenure track or nontenure, and expectations for promotion may vary greatly depending on the type of department, track, and the AHC. In this article, the authors identify strategies for developing early-stage CBFs in four domains: (1) Influence of department/environment, (2) Skills to develop, (3) Ways to increase productivity, and (4) Ways to document accomplishments. Graduating students and postdoctoral fellows should consider the first domain when choosing a faculty position. Early-stage CBFs will benefit by understanding the requirements of their environment early in their appointment and by modifying the provided progression grid with their chair and mentoring team as needed. Following this personalized grid will increase the chances of a satisfying career with appropriate recognition for academic accomplishments.     

Enhancing statistical education by using role-plays of consultations

Summary.  Role-plays in which students act as clients and statistical consultants to each other in pairs have proved to be an effective class exercise. As well as helping to teach statistical methodology, they are effective at encouraging statistical thinking, problem solving, the use of context in applied statistical problems and improving attitudes towards statistics and the statistics profession. Furthermore, they are fun. This paper explores the advantages of using role-plays and provides some empirical evidence supporting their success. The paper argues that there is a place for teaching statistical consulting skills well before the traditional post-graduate qualification in statistics, including to school students with no knowledge of techniques in statistical inference.     

A Question of Ethics

This article identifies three consulting roles—helper, leader, and colleague; recommends that statistical consultants ask more questions about basic mechanisms; suggests that statistical consultants regard their primary responsibility as providing guidance about the scientific method itself; discusses the need for continuing education to help improve consulting skills; and describes Wisconsin's Master's degree examination, which was designed to help students become effective practicing statisticians.     

Questions and Answers

In addition to his contributions to biostatistics and clinical trials, Paul Meier had a long-term interest in the legal applications of statistics. As part of this, he had extensive experience as a statistical consultant. Legal consulting can be a minefield, but as a result of his background, Paul had excellent advice to give to those starting out on how to function successfully in this environment.     

Seeking useful contribution

This short communication is an attempt to define useful contribution in statistical consulting and to connect it to a collection of favorable attitudes and skills. It stresses the need for adequate education of beginning statisticians to render them capable of contributing effectively to society, business, and research. The communication ends with a list of related articles and publications.     

A proposal for a new PhD level curriculum on quantitative methods for drug development

This paper provides an overview of “Improving Design, Evaluation and Analysis of early drug development Studies” (IDEAS), a European Commission–funded network bringing together leading academic institutions and small‐ to large‐sized pharmaceutical companies to train a cohort of graduate‐level medical statisticians. The network is composed of a diverse mix of public and private sector partners spread across Europe, which will host 14 early‐stage researchers for 36 months. IDEAS training activities are composed of a well‐rounded mixture of specialist methodological components and generic transferable skills. Particular attention is paid to fostering collaborations between researchers and supervisors, which span academia and the private sector. Within this paper, we review existing medical statistics programmes (MSc and PhD) and highlight the training they provide on skills relevant to drug development. Motivated by this review and our experiences with the IDEAS project, we propose a concept for a joint, harmonised European PhD programme to train statisticians in quantitative methods for drug development.     

Best Practices for Biostatistical Consultation and Collaboration in Academic Health Centers

Given the increasing level and scope of biostatistics expertise needed at academic health centers today, we developed best practices guidelines for biostatistics units to be more effective in providing biostatistical support to their institutions, and in fostering an environment in which unit members can thrive professionally. Our recommendations focus on the key areas of: (1) funding sources and mechanisms; (2) providing and prioritizing access to biostatistical resources; and (3) interacting with investigators. We recommend that the leadership of biostatistics units negotiate for sufficient long-term infrastructure support to ensure stability and continuity of funding for personnel, align project budgets closely with actual level of biostatistical effort, devise and consistently apply strategies for prioritizing and tracking effort on studies, and clearly stipulate with investigators prior to project initiation policies regarding funding, lead time, and authorship.     

Preparing Statisticians for Careers in Industry: Report of the ASA Section on Statistical Education Committee on Training of Statisticians for Industry

This report provides guidelines for universities to consider in developing programs for training statisticians who will work in industry. Useful information for students who are considering industrial employment is also included. The recommended programs focus on real problems and the statistical theory and methodology that are useful in their solution. Technical competence is only one of many factors that industry considers when hiring and promoting statisticians. When a statistician leaves school, his or her skills and experiences should include statistical knowledge, practical problem solving, consulting practice, and the ability to communicate orally and in writing with nonstatisticians. There are many details that must be worked out (e.g., content of specific courses and organization of consulting internship programs), and it is hoped that the statistical societies and universities will form committees, hold conferences, and develop programs to address these issues further. Many of our recommendations apply more broadly to the training of all types of practicing statisticians.     

Ethical Numbers: Ethics Training in U.S. Graduate Statistics Programs, 2013–2014

As important members of research teams, statisticians bear an ethical responsibility to analyze, interpret, and report data honestly and objectively. One way of reinforcing ethical responsibilities is through required courses covering a variety of ethics-related topics at the graduate level. We assessed ethics requirements for graduate-level statistics training programs in the United States for the 2013–2014 academic year using the websites of 88 universities, examining 103 biostatistics programs, and 136 statistics degree programs. We categorized programs’ ethics training requirements as required or not required. Thirty-one (35.1%) universities required an ethics course for at least some degree students. Sixty-two (25.5%) degree programs required an ethics course for at least some students. The majority (77.4%) of required courses were worth 0 or 1 credit. Of the 177 programs without an ethics requirement, 19 (10.7%) listed an ethics elective. Although a single ethics course is insufficient for instilling an ethical approach to science, degree programs that model expectations through coursework point to the value of ethics in science. More training programs should prepare statisticians to consider the ethical dimensions of their work through required coursework. Supplementary materials for this article are available online.     

A Bayesian Analysis of Synchronous Distance Learning versus Matched Traditional Control in Graduate Biostatistics Courses

Distance learning can be useful for bridging geographical barriers to education in rural settings. However, empirical evidence on the equivalence of distance education and traditional face-to-face (F2F) instruction in statistics and biostatistics is mixed. Despite the difficulty in randomization, we minimized intra-instructor variation between F2F and online sections in seven graduate-level biostatistics service courses in a synchronous (live, real time) fashion; that is, for each course taught in a traditional F2F setting, a separate set of students were taught simultaneously via online learning technology, allowing for two-way interaction between instructor and students. Our primary objective was to compare student performance in the two courses that use these two teaching modes. We used a Bayesian hierarchical model to test equivalence of modes. The frequentist mixed model approach was also conducted for reference. The results of Bayesian and frequentist methods agree and suggest a difference of less than 1% in average final grades. Finally, we discuss barriers to instruction and learning using the applied online teaching technology.     

Graduate Statistics Service Courses

This article describes our experience in, and recommendations for, teaching introductory statistics service courses to graduate students. Drawing on the student's research orientation, the instructor can present statistics as a valuable component of the scientific method, using examples from the student's particular discipline(s). Statistically qualified course instructors may be affiliated with statistics or other departments, and the course may be offered within any department. Course goals can range from training students to function independently as statistical analysts in future research to training students to consult a qualified statistician about design and analysis issues.     

Maintaining the Professional Integrity of Federal Statistics

Transactional analysis can be used to analyze personal interactions between consulting statisticians and their clients. The Parent-Adult-Child model has recently been refined to consist of six states by subdividing the Parent and Child ego states. The authors briefly define the six ego states (Nurturing Parent, Critical Parent, Adult, Adapted Child, Free Child, and Rebellious Child) and describe their occurrence during statistical consultations. Recommendations are given for identifying the ego states, setting realistic goals for relationships, and modifying unsatisfactory transactions.     

My life as a statistician * **

This article was written for a keynote speech to present a few highlights of my life as a statistician. It has seven sections beginning with an introduction in Section 17 some prospects of biostatistics in Section 2, and a tribute to J. Neyman in Section 3. In Section 4 is a sample of my work including motivation for my studies on the life table and competing risks, contributions and comments in survival analyses, a solution for Kolmogorov differential equations, and an explicit formula for the n-step transition probability in discrete time Markov chains.     

Statistical Mentoring at Early Training and Career Stages

At Los Alamos National Laboratory (LANL), statistical scientists develop solutions for a variety of national security challenges through scientific excellence, typically as members of interdisciplinary teams. At LANL, mentoring is actively encouraged and practiced to develop statistical skills and positive career-building behaviors. Mentoring activities targeted at different career phases from student to junior staff are an important catalyst for both short and long term career development. This article discusses mentoring strategies for undergraduate and graduate students through internships as well as for postdoctoral research associates and junior staff. Topics addressed include project selection, progress, and outcome; intellectual and social activities that complement the student internship experience; key skills/knowledge not typically obtained in academic training; and the impact of such internships on students’ careers. Experiences and strategies from a number of successful mentorships are presented. Feedback from former mentees obtained via a questionnaire is incorporated. These responses address some of the benefits the respondents received from mentoring, helpful contributions and advice from their mentors, key skills learned, and how mentoring impacted their later careers.     

Teaching Statistical Consulting Before Statistical Methodology

This paper outlines and discusses the advantages of an ‘Introduction to Statistical Consulting’ course (ISC) that exposes students to statistical consulting early in their studies. The course is intended for students before, or while, they study their units in statistical techniques, and assumes only a first‐year introductory statistics unit. The course exposes undergraduate students to the application of statistics and helps develop statistical thinking. An important goal is to introduce students to work as a statistician early in their studies because this motivates some students to study statistics further and provides a framework to motivate the learning of further statistical techniques. The ISC has proved popular with students, and this paper discusses the reasons for this popularity and the benefits of an ISC to statistical education and the statistics profession.